Abstract. Magnetic Resonance Imaging (MRI) has become a cornerstone in medical diagnostics due to its superior soft tissue contrast and non-invasive nature. However, the complexity and vast amount of data generated by MRI necessitate advanced digital processing techniques to enhance image quality, facilitate interpretation, and extract meaningful clinical information. This article provides a comprehensive overview of the current methods employed in the digital processing of MRI images. Key topics include preprocessing techniques such as noise reduction and artifact correction, image segmentation, feature extraction, and advanced reconstruction methods. We also explore the application of machine learning algorithms in enhancing diagnostic accuracy and efficiency. By integrating these digital processing methods, MRI technology can significantly improve patient outcomes through more precise and reliable imaging.